Jednotky: Transfer learning and hybrid deep convolutional neural networks models for autism spectrum disorder classification from EEG signals

Transfer learning and hybrid deep convolutional neural networks models for autism spectrum disorder classification from EEG signals

Autism spectrum disorder (ASD) is a developmental disease characterised by restricted and repetitive behaviours, as well as difficulty in social communication and interaction, in children. The clinical diagnosis of ASD is reached by behavioural screening, which delays early intervention. Electroence...

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Hlavní autoři:	Al-Qazzaz, Noor Kamal, Aldoori, Alaa A., Buniya, Ali K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom
Médium:	Článek
Jazyk:	English
Vydáno:	Institute of Electrical and Electronics Engineers 2024
On-line přístup:	http://psasir.upm.edu.my/id/eprint/111550/1/Transfer_Learning_and_Hybrid_Deep_Convolutional_Neural_Networks_Models_for_Autism_Spectrum_Disorder_Classification_From_EEG_Signals.pdf
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http://psasir.upm.edu.my/id/eprint/111550/1/Transfer_Learning_and_Hybrid_Deep_Convolutional_Neural_Networks_Models_for_Autism_Spectrum_Disorder_Classification_From_EEG_Signals.pdf

Transfer learning and hybrid deep convolutional neural networks models for autism spectrum disorder classification from EEG signals

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